Rapid framework for quantitative magnetization transfer imaging with interslice magnetization transfer and dictionary-driven fitting approaches

Abstract

Purpose: To develop a rapid framework for quantitative magnetization transfer (qMT) imaging based on the 2D interslice MT and dictionary-driven fitting approaches. Methods: Sequential balanced steady-state free precession (bSSFP) scanning was performed on a whole human brain in a total of 12 conditions from six different interslice gaps and two different flip angles. To obtain qMT maps, the acquired 12 datasets were fitted to a dictionary predefined by using Bloch equation simulations based on the two-pool MT model. The proposed qMT method was compared to the conventional qMT methods, in terms of qMT parameter maps and processing time. Results: The proposed method yielded qMT maps similar to those of the conventional method, indicating feasibility of modulating MT saturation frequency and power with the interslice gap and flip angle. The whole-brain qMT imaging could be completed in 8 min because of the absence of separate MT pulses. The time for processing qMT parameters was significantly reduced through the dictionary-driven approach; it is 1000 times shorter than that without the dictionary-driven approach and 3 times shorter than that with the spoiled gradient recalled echo-qMT method that uses an analytical solution. Conclusion: The proposed dictionary-driven interslice qMT imaging provides qMT maps close to those from the conventional method with significantly reduced scan time and postprocessing time, which can make qMT imaging more clinically acceptable.